EXCELLENT UIPATH-SAIAV1 PDF DUMPS FILES FOR REAL EXAM

Excellent UiPath-SAIAv1 PDF Dumps Files for Real Exam

Excellent UiPath-SAIAv1 PDF Dumps Files for Real Exam

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UiPath Specialized AI Associate Exam (2023.10) Sample Questions (Q26-Q31):

NEW QUESTION # 26
What is a reason for pinning a UiPath Communications Mining Model?

  • A. To allow AB comparing of the statistics of that model version with another one.
  • B. To delete all other model versions.
  • C. To allow rollback of annotations to that model version.
  • D. To force the Ul to show predictions from that model version in explore

Answer: D

Explanation:
In UiPath Communications Mining, pinning a model ensures that the predictions shown in the Explore tab are generated from that specific model version. This feature allows users to control which version of the model is actively making predictions, particularly during evaluation or comparison stages. By pinning a model, the user ensures that the UI reflects the predictions from the selected version, helping maintain consistency when analyzing results or making changes.
For more details, refer to:
UiPath Communications Mining: Model Management and Pinning
UiPath AI Center Documentation: Managing Model Versions


NEW QUESTION # 27
What is the minimum number of pinned examples users should provide per label in UiPath Communications Mining?

  • A. 0
  • B. 1
  • C. 2
  • D. 3

Answer: D

Explanation:
Mining, it is recommended that users provide a minimum of 25 pinned examples per label to ensure proper training and accurate predictions by the machine learning models. This number allows the platform to have a sufficient variety of examples to generalize and make reliable predictions for each label in real-world scenarios.
The minimum number of pinned examples per label is crucial because it enhances both precision and recall, helping the model effectively differentiate between labels and improving overall model performance. If fewer examples are provided, the model may struggle with generalization and might not perform well in distinguishing between similar or overlapping categories.
This standard of 25 pinned examples is outlined in several UiPath documentation sections and best practices for training models in Communications Mining UiPath Documentation UiPath Documentation UiPath Community Forum For further details, refer to UiPath's official Communications Mining User Guide on their documentation portal.


NEW QUESTION # 28
What can the Sentiment Analysis out-of-the-box model be used for?

  • A. Relate customer questions to FAQ documents and automatically pull responses from these documents.
  • B. Understand the emotion in product reviews, customer surveys, social media posts, and emails.
  • C. Classify text in resumes, emails, web pages, and other formats.
  • D. Extract and classify text in emails, letters, web pages, research papers, and call transcripts.

Answer: B

Explanation:
The Sentiment Analysis out-of-the-box model in UiPath is used to interpret and classify the emotional tone within text data. It is particularly useful for analyzing product reviews, customer feedback, social media posts, and emails to understand customer sentiment and emotional responses, helping businesses make informed decisions based on these insights.(Source: UiPath Sentiment Analysis model documentation


NEW QUESTION # 29
A Document Understanding Process is in production. According to best practices, what are the locations recommended for exporting the result files?

  • A. Locally, Temp Folder, Network Attached Storage, and Orchestrator Bucket.
  • B. On a VM, Orchestrator Bucket, and Network Attached Storage.
  • C. Orchestrator Bucket and Queue Item.
  • D. Network Attached Storage and Orchestrator Bucket.

Answer: D

Explanation:
In a Document Understanding Process, particularly when it is in production, it is crucial to manage output data securely and efficiently. Utilizing Network Attached Storage (NAS) and Orchestrator Buckets are recommended practices for exporting result files for several reasons:
Network Attached Storage (NAS): NAS is a dedicated file storage that allows multiple users and client devices to retrieve data from centralized disk capacity. Using NAS in a production environment for storing result files is beneficial due to its accessibility, capacity, and security features. It facilitates easy access and sharing of files within a network while maintaining data security.
Orchestrator Bucket: Orchestrator Buckets in UiPath are used for storing files that can be easily accessed by the robots. This is particularly useful in a production environment because it provides a centralized, cloud- based storage solution that is scalable, secure, and accessible from anywhere. This aligns with the best practices of maintaining high availability and security for business-critical data.
The other options (B, C, and D) include locations that might not be as secure or efficient for a production environment. For example, storing files locally or in a temp folder can pose security risks and is not scalable for large or distributed systems. Similarly, storing directly on a VM might not be the most efficient or secure method, especially when dealing with sensitive data.


NEW QUESTION # 30
What is DOM in the context of Document Understanding?

  • A. Digitize Object Module is an XML object containing information such as mandatory field names, types, and values
  • B. Digitized Object Model is an XML object containing information such as page data, content, and coordinates for every image identified in the file.
  • C. Data Object Model is a YAML object containing information such as name, content type, text length, and the number of pages.
  • D. Document Object Model is a JSON object containing information such as name, content type, text length, and the number of pages.

Answer: B

Explanation:
In UiPath Document Understanding, the Digitized Object Model (DOM) is an XML structure that contains detailed information about the document being processed. This includes data such as the content of each page, the coordinates of each element within the document, and additional metadata. The DOM is created during the digitization process, where scanned or image-based documents are converted into machine-readable formats for further processing, such as classification and data extraction.
For more details, refer to:
UiPath Document Understanding Documentation: Digitization and the DOM
Digitize Document Activity: Working with DOM


NEW QUESTION # 31
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